• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.724-730
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• 1993

Most of clustering methods usually employ the center of a cluster to assign the input data into a cluster. When the shape of a cluster could not be easily represented by the center of cluster, however, it is difficult to assign input data into a proper cluster using previous methods. In this paper, to overcome such a difficulty, a cluster is to be represented as a collection of several subclusters. And membership functions are used to represent how much input data belong to subclusters. Then the position of each subcluster is adoptively corrected by use of a competitive learning neural network. To show the validity of the proposed method, a numerical example is illustrated, where FMMC(Fuzzy Min-Max Clustering) algorithm is compared with the proposed method.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.60.3-61
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• 2018

Abell 115 is a renowned cluster merger at z=0.197. It exhibits an asymmetric X-ray distribution with cometary tails and a megaparsec-sized radio relic stretching in the northeastern direction from the core of the northern cluster. Many observations have concluded that this cluster merger has a large impact parameter, but there has been no numerical analysis on the structure of Abell 115. In this study, we simulate Abell 115 with Gadget2 N-body/SPH code to reproduce the X-ray and weak lensing features of Abell 115. We find a new plausible merger scenario of Abell 115, wherein the northern cluster is currently in an outgoing phase. The predicted X-ray emission has a similar morphology to the observed tail of the northern cluster. However, in order to reproduce the observed line-of-sight velocity and projected distance while maintaining the two systems gravitationally bound, the system should possess a large projection angle, which makes the shock look considerably more diffused than the observed radio relic.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.99-102
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• 2003

본 논문에서는 퍼지 클러스터링 알고리즘에 의해 구해진 퍼지 클러스터들에 대한 평가척도를 제안한다. 제안된 척도는 퍼 지 클러스터들간의 중첩성(overlapping)과 분리성 (separation)을 이용한다. 중첩성은 클러스터간 인접도를 이용하여 계산하며, 분리성은 데이터에 대한 상관성 정도를 나타낸다. 따라서 중첩성이 낮고 분리성이 높을수록 좋은 클러스터 결과라고 할 수 있다. 표준 데이터 집합을 대상으로 기존의 척도들과 비교실험 함으로써 제안된 척도의 신뢰성을 알아보았다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.288-291
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• 2008

본 논문은 실수 진화 알고리즘에 대해서 가상의 클러스터를 이용한 재조합 연산자 및 새로운 세대차 모델을 소개한다. 가상 클러스터의 자가 적응적인 크기 변화를 통해 자손의 생성범위를 적절히 조절하고, 선택과 대치를 포함한 진화방식을 개선하여 효율적인 세대차 크기를 구함으로서, 개체의 다양성 유지 및 탐색성능의 향상을 꾀하였다. 제안된 방법을 벤치마크 테스트 문제에 적용하여 G3 알고리즘과 CMA-ES 등과 성능을 비교하였다.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.25-33
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• 1992

Manufacturing cell formation is one of the most important problems faced in designing cellular manufacturing systems. The purpose of this study is to design effective manufacturing cell systems by developing a method which forms machines/parts into optimal machine cells/part families. The 0-1 data matrix structure is used to form a basis for manufacturing cell formation. In this paper, we propose a CE method to reorder the 0-1 data matrix for manufacturing cell formation. The resulting solutions are shown to demonstrate the effectiveness of the CE method.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.557-563
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• 2000

We introduce r-fuzzy $\delta$-cluster ($\theta$-cluster) points and r-fuzzy $\delta$-closure ($\theta$-closure) sets in smooth fuzzy topological spaces in a view of the definition of A.P. Sostak [13]. We study some properties of them.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.106-113
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• 2000

본 논문은 다량우편물의 대부분을 차지하는 창이 있는 봉투와 최근 증가되고 있는 명도 값이 높은 색깔이 있는 우편봉투 영상에서 구조적 방법을 분석하여 수취인 주소 영역을 자동적으로 추출하고 추출된 영역에서 우편번호를 찾아 제안된 신경망으로 인식 및 검증할 수 있는 실용적인 시스템을 구현하였다.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.928-938
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• 2008

This study presents an approach for approximation an unknown function from a numerical data set based on the synthesis of a neuro-fuzzy model. An adaptive input data space parting method, which is used for building hyperbox-shaped clusters in the input data space, is proposed. Each data cluster is implemented here as a fuzzy set using a membership function MF with a hyperbox core that is constructed from a min vertex and a max vertex. The focus of interest in proposed approach is to increase degree of fit between characteristics of the given numerical data set and the established fuzzy sets used to approximate it. A new cutting procedure, named NCP, is proposed. The NCP is an adaptive cutting procedure using a pure function $\Psi$ and a penalty function $\tau$ for direction the input data space parting process. New algorithms named CSHL, HLM1 and HLM2 are presented. The first new algorithm, CSHL, built based on the cutting procedure NCP, is used to create hyperbox-shaped data clusters. The second and the third algorithm are used to establish adaptive neuro- fuzzy inference systems. A series of numerical experiments are performed to assess the efficiency of the proposed approach.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 1997.11a
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• pp.104-111
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• 1997

Cluster systems are microcrystals of vanadiumoxided compounds such as Barium, Calcium or Sodium Metavanadates or Sodium Vanadium Bronze which are distributed into dimethyl- or diethylphosphites or microcrystals of vanadium oxides, for instance, vanadium oxide (+3), distributed into the methylphosphonic acid melted. During the interaction of vanadium compounds with the correspondent phosphororganic substances biue viscous liquids are formed. These liquids have paramagnetic properties. According to the UV and IR spectroscopic investigations as well as the results of EPR spectra the substances obtained consist of the nucleus containing 6 to 12 of vanadium atoms and the shell including ligands which are molecules of phosphites or methylphosphonic acid. Here every atom of vanadium interacts with four of phosphorus containing molecules. Sizes of the particles in these systems donot exceed 200 nm. Introduction of cluster systems (0,1 -0,3 % vanadium) into epoxy compositions before the introduction of curing agent - polyethylenepolyamine 6 -8 % leads to the acceleration of composition crosslinking and to the combustion decreasing: 1) Oxygen Index grows to 35: 2)mass losses during combustion decrease to 1-2%, 3) combustion time does not exceed 1 s; 4) the intumescence of material sample is being observed during the burner action as well as the foam coke formation.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.517-524
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• 2004

The fuzzy set theory has been wide used in clustering of machine learning with data mining since fuzzy theory has been introduced in 1960s. In particular, fuzzy C-means algorithm is a popular fuzzy clustering algorithm up to date. An element is assigned to any cluster with each membership value using fuzzy C-means algorithm. This algorithm is affected from the location of initial cluster center and the proper cluster size like a general clustering algorithm as K-means algorithm. This setting up for initial clustering is subjective. So, we get improper results according to circumstances. In this paper, we propose a cluster merging using enhanced density based fuzzy C-means clustering algorithm for solving this problem. Our algorithm determines initial cluster size and center using the properties of training data. Proposed algorithm uses grid for deciding initial cluster center and size. For experiments, objective machine learning data are used for performance comparison between our algorithm and others.